add leaderboard

README.md

@@ -20,6 +20,7 @@ language:
 - <a href="https://www.nexa4ai.com/" target="_blank">Nexa AI Website</a>
 - <a href="https://github.com/NexaAI/octopus-v4" target="_blank">Octopus-v4 Github</a>
 - <a href="https://arxiv.org/abs/2404.19296" target="_blank">ArXiv</a>
+- <a href="https://huggingface.co/spaces/NexaAIDev/domain_llm_leaderboard" target="_blank">Domain LLM Leaderbaord</a>
 - <a href="https://graph.nexa4ai.com/" target="_blank">Graph demo</a>
 </p>
 
@@ -118,6 +119,7 @@ We leverage the latest Language Large Models for a variety of domains. Below is
 | `AdaptLLM/law-chat`                     | Law                | `international_law`, `jurisprudence`, `professional_law`                                                                                                         |
 | `meta-llama/Meta-Llama-3-8B-Instruct`   | Psychology         | `high_school_psychology`, `professional_psychology`                                                                                                              |
 
+
 ### MMLU Benchmark Results (5-shot learning)
 Here are the comparative MMLU scores for various models tested under a 5-shot learning setup:
 
@@ -131,7 +133,8 @@ Here are the comparative MMLU scores for various models tested under a 5-shot le
 | Gemma-2b                          | 42.3%          |
 | Gemma-7b                          | 64.3%          |
 
-
+###  Domain LLM Leaderboard
+Explore our collection of domain-specific large language models (LLMs) or contribute by suggesting new models tailored to specific domains. For detailed information on available models and to engage with our community, please visit our [Domain LLM Leaderboard](https://huggingface.co/spaces/NexaAIDev/domain_llm_leaderboard).
 
 ## References
 We thank the Microsoft team for their amazing model!